Comparison of Glomerular Filtration Rate Equations in a Rural New Mexico Cohort: Results from the COMPASS Study

Abstract

Rationale and ObjectiveThe NKF-ASN Task Force recommends accurate kidney function estimation avoiding biases through racial adjustments. We explored the use of multiple kidney function biomarkers and hence estimated glomerular filtration rate (eGFR) equations to improve kidney function calculations in an ethnically diverse patient population.Study designProspective community cohort study.Setting and ParticipantsRural New Mexico clinic with patients > 18 yo.MethodsMarkers of kidney function, IDMS-Creatinine (SCr), chemiluminescence Beta-2 Microglobulin (B2M), Nephelometry-calibrated ELISA Cystatin C (CysC), inflammation, glucose tolerance, demographics, BUN/UACR from the baseline visit of the COMPASS cohort, were analyzed by Kernel-based Virtual Machine learning methods.ResultsAmong 205 participants, the mean age was 50.1, 62% were female, 54.1% Hispanic American and 30.2% Native American. Average kidney function biomarkers were: SCr 0.9 mg/dl, B2M 1.8 mg/L, and CysC 0.7 mg/dl. The highest agreement was observed between SCr and B2M-based eGFR equations [mean difference in eGFRs: (4.48 ml/min/1.73m2], and the lowest agreement between B2M and CysC-based eGFR equations (−24.75 ml/min/1.73m2). There was no pattern of association between the differences in eGFR measures and gender. In the continuous analyses, the absolute eGFR value (p<2 × 10-16) and serum albumin (p =6.4 × 10-5) predicted the difference between B2M- and SCr-based e-GFR. The absolute eGFR value (p<2 × 10-16) and age (p =7.6 x 10-5) predicted the difference between CysC- and SCr-based e-GFR.LimitationsRelatively small sample size, elevated inflammatory state in majority of study participants and no inulin excretion rate measurements.ConclusionB2M should be strongly considered as a kidney function biomarker fulfilling the criteria for the NKF-ASN. B2M’s eGFR equation does not need adjustment for gender or race and showed the highest agreement with SCr-based eGFR equations.